Fraunhofer Project Group for Automation in Medicine and Biotechnology

Mannheim, Germany

Fraunhofer Project Group for Automation in Medicine and Biotechnology

Mannheim, Germany
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Theuring M.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Dimitriadis N.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Grychtol B.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Deliolanis N.C.,Fraunhofer Project Group for Automation in Medicine and Biotechnology
Optics InfoBase Conference Papers | Year: 2016

We demonstrate an imaging system intended for medical applications that allows to display simultaneously and in real-time both the reflectance image as well as the signal from up to three fluorescent dyes. © OSA 2016.


Grychtol B.,German Cancer Research Center | Grychtol B.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Adler A.,Carleton University
Physiological Measurement | Year: 2014

Electrical impedance tomography (EIT) estimates an image of change in electrical properties within a body from stimulations and measurements at surface electrodes. There is significant interest in EIT as a tool to monitor and guide ventilation therapy in mechanically ventilated patients. In lung EIT, the EIT inverse problem is commonly linearized and only changes in electrical properties are reconstructed. Early algorithms reconstructed changes in resistivity, while most recent work using the finite element method reconstructs conductivity. Recently, we demonstrated that EIT images of ventilation can be misleading if the electrical contrasts within the thorax are not taken into account during the image reconstruction process. In this paper, we explore the effect of the choice of the reconstructed electrical properties (resistivity or conductivity) on the resulting EIT images. We show in simulation and experimental data that EIT images reconstructed with the same algorithm but with different parametrizations lead to large and clinically significant differences in the resulting images, which persist even after attempts to eliminate the impact of the parameter choice by recovering volume changes from the EIT images. Since there is no consensus among the most popular reconstruction algorithms and devices regarding the parametrization, this finding has implications for potential clinical use of EIT. We propose a program of research to develop reconstruction techniques that account for both the relationship between air volume and electrical properties of the lung and artefacts introduced by the linearization. © 2014 Institute of Physics and Engineering in Medicine.


Biguri A.,University of Bath | Grychtol B.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Adler A.,Carleton University | Soleimani M.,University of Bath
Physiological Measurement | Year: 2015

Electrical impedance tomography (EIT) has shown significant promise for lung imaging. One key challenge for EIT in this application is the movement of electrodes during breathing, which introduces artefacts in reconstructed images. Various approaches have been proposed to compensate for electrode movement, but no comparison of these approaches is available. This paper analyses boundary model mismatch and electrode movement in lung EIT. The aim is to evaluate the extent to which various algorithms tolerate movement, and to determine if a patient specific model is required for EIT lung imaging. Movement data are simulated from a CT-based model, and image analysis is performed using quantitative figures of merit. The electrode movement is modelled based on expected values of chest movement and an extended Jacobian method is proposed to make use of exterior boundary tracking. Results show that a dynamical boundary tracking is the most robust method against any movement, but is computationally more expensive. Simultaneous electrode movement and conductivity reconstruction algorithms show increased robustness compared to only conductivity reconstruction. The results of this comparative study can help develop a better understanding of the impact of shape model mismatch and electrode movement in lung EIT. © 2015 Institute of Physics and Engineering in Medicine.


Gagnon H.,Carleton University | Grychtol B.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Adler A.,Carleton University
Physiological Measurement | Year: 2015

Electrical impedance tomography (EIT) provides low-resolution images of internal conductivity distributions, but is able to achieve relatively high temporal resolutions. Most EIT image reconstruction algorithms do not explicitly account for the temporal constraints on the measurements or physiological processes under investigation. Instead, algorithms typically assume both that the conductivity distribution does not change during the acquisition of each EIT data frame, and that frames can be reconstructed independently, without consideration of the correlation between images. A failure to account for these temporal effects will result in aliasing-related artefacts in images. Several methods have been proposed to compensate for these effects, including interpolation of raw data, and reconstruction algorithms using Kalman and temporal filtering. However, no systematic work has been performed to understand the severity of the temporal artefacts nor the extent to which algorithms can account for them. We seek to address this need by developing a temporal comparison framework and figures of merit to assess the ability of reconstruction algorithms to account for temporal effects. Using this approach, we compare combinations of three reconstruction algorithms using three EIT data frame types: perfect, realistic and interpolated. The results show that, without accounting for temporal effects, artefacts are present in images for dynamic conductivity contrasts at frequencies 10-20 times slower than the frame rate. The proposed methods show some improvements in reducing these artefacts. © 2015 Institute of Physics and Engineering in Medicine.


Grychtol B.,German Cancer Research Center | Grychtol B.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Elke G.,University of Kiel | Meybohm P.,University Hospital Frankfurt | And 3 more authors.
PLoS ONE | Year: 2014

Introduction: Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited. Methods: We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data. Results and Conclusions: Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT. © 2014 Grychtol et al.


PubMed | Polytechnic of Milan, Murdoch Childrens Research Institute, Carleton University, University of Milan and 2 more.
Type: Journal Article | Journal: American journal of physiology. Lung cellular and molecular physiology | Year: 2016

Respiratory transition at birth involves rapidly clearing fetal lung liquid and preventing efflux back into the lung while aeration is established. We have developed a sustained inflation (SI


Deliolanis N.C.,Helmholtz Center Munich | Deliolanis N.C.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Ale A.,Helmholtz Center Munich | Morscher S.,Helmholtz Center Munich | And 7 more authors.
Molecular Imaging and Biology | Year: 2014

Purpose: A primary enabling feature of near-infrared fluorescent proteins (FPs) and fluorescent probes is the ability to visualize deeper in tissues than in the visible. The purpose of this work is to find which is the optimal visualization method that can exploit the advantages of this novel class of FPs in full-scale pre-clinical molecular imaging studies. Procedures: Nude mice were stereotactically implanted with near-infrared FP expressing glioma cells to from brain tumors. The feasibility and performance metrics of FPs were compared between planar epi-illumination and trans-illumination fluorescence imaging, as well as to hybrid Fluorescence Molecular Tomography (FMT) system combined with X-ray CT and Multispectral Optoacoustic (or Photoacoustic) Tomography (MSOT). Results: It is shown that deep-seated glioma brain tumors are possible to visualize both with fluorescence and optoacoustic imaging. Fluorescence imaging is straightforward and has good sensitivity; however, it lacks resolution. FMT-XCT can provide an improved rough resolution of ∼1 mm in deep tissue, while MSOT achieves 0.1 mm resolution in deep tissue and has comparable sensitivity. Conclusions: We show imaging capacity that can shift the visualization paradigm in biological discovery. The results are relevant not only to reporter gene imaging, but stand as cross-platform comparison for all methods imaging near infrared fluorescent contrast agents. © 2014 World Molecular Imaging Society.


Tzoumas S.,Helmholtz Center Munich | Deliolanis N.,Helmholtz Center Munich | Deliolanis N.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Morscher S.,Helmholtz Center Munich | And 2 more authors.
IEEE Transactions on Medical Imaging | Year: 2014

Detection of intrinsic or extrinsically administered chromophores and photo-absorbing nanoparticles has been achieved by multi-spectral optoacoustic tomography (MSOT). The detection sensitivity of MSOT depends not only on the signal to noise ratio considerations, as in conventional optoacoustic (photoacoustic) tomography implementations, but also on the ability to resolve the molecular targets of interest from the absorbing tissue background by means of spectral unmixing or sub-pixel detection methods. However, it is not known which unmixing methods are optimally suited for the characteristics of multispectral optoacoustic images. In this work we investigated the performance of different sub-pixel detection methods, typically used in remote sensing hyperspectral imaging, within the context of MSOT. A quantitative comparison of the different algorithmic approaches was carried out in an effort to identify methods that operate optimally under the particulars of molecular imaging applications. We find that statistical sub-pixel detection methods can demonstrate a unique detection performance with up to five times enhanced sensitivity as compared to linear unmixing approximations, under the condition that the optical agent of interest is sparsely present within the tissue volume, as common when using targeted agents and reporter genes. © 1982-2012 IEEE.


Ale A.,Helmholtz Center Munich | Ale A.,Imperial College London | Ermolayev V.,Helmholtz Center Munich | Deliolanis N.C.,Helmholtz Center Munich | And 2 more authors.
Journal of Biomedical Optics | Year: 2013

The ability to visualize early stage lung cancer is important in the study of biomarkers and targeting agents that could lead to earlier diagnosis. The recent development of hybrid free-space 360-deg fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) imaging yields a superior optical imaging modality for three-dimensional small animal fluorescence imaging over stand-alone optical systems. Imaging accuracy was improved by using XCT information in the fluorescence reconstruction method. Despite this progress, the detection sensitivity of targeted fluorescence agents remains limited by nonspecific background accumulation of the fluorochrome employed, which complicates early detection of murine cancers. Therefore we examine whether x-ray CT information and bulk fluorescence detection can be combined to increase detection sensitivity. Correspondingly, we research the performance of a data-driven fluorescence background estimator employed for subtraction of background fluorescence from acquisition data. Using mice containing known fluorochromes ex vivo, we demonstrate the reduction of background signals from reconstructed images and sensitivity improvements. Finally, by applying the method to in vivo data from K-ras transgenic mice developing lung cancer, we find small tumors at an early stage compared with reconstructions performed using raw data. We conclude with the benefits of employing fluorescence subtraction in hybrid FMT-XCT for early detection studies. © 2013 Society of Photo-Optical Instrumentation Engineers.


Tzoumas S.,TU Munich | Nunes A.,TU Munich | Deliolanis N.C.,Fraunhofer Project Group for Automation in Medicine and Biotechnology | Ntziachristos V.,TU Munich
Journal of Biophotonics | Year: 2015

Molecular optoacoustic (photoacoustic) imaging typically relies on the spectral identification of absorption signatures from molecules of interest. To achieve this, two or more excitation wavelengths are employed to sequentially illuminate tissue. Due to depth-related spectral dependencies and detection related effects, the multispectral optoacoustic tomography (MSOT) spectral unmixing problem presents a complex non-linear inversion operation. So far, different studies have showcased the spectral capacity of optoacoustic imaging, without however relating the performance achieved to the number of wavelengths employed. Overall, the dependence of the sensitivity and accuracy of optoacoustic imaging as a function of the number of illumination wavelengths has not been so far comprehensively studied. In this paper we study the impact of the number of excitation wavelengths employed on the sensitivity and accuracy achieved by molecular optoacoustic tomography. We present a quantitative analysis, based on synthetic MSOT datasets and observe a trend of sensitivity increase for up to 20 wavelengths. Importantly we quantify this relation and demonstrate an up to an order of magnitude sensitivity increase of multi-wavelength illumination vs. single or dual wavelength optoacoustic imaging. Examples from experimental animal studies are finally utilized to support the findings. In vivo MSOT imaging of a mouse brain bearing a tumor that is expressing a near-infrared fluorescent protein. (a) Monochromatic optoacoustic imaging at the peak excitation wavelength of the fluorescent protein. (b) Overlay of the detected bio-distribution of the protein (red pseudocolor) on the monochromatic optoacoustic image. (c) Ex vivo validation by means of cryoslicing fluorescence imaging. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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